Senior Machine Learning Engineer - Scene Understanding
Develops advanced Vision-Language-Action models for robotaxi scene understanding, detecting hazards and enabling safe driving. Leads data strategies, post-training of large models, and deployment using PyTorch and production ML pipelines. Requires MS/PhD in CS and deep learning expertise.
189k – 290k
HybridML Engineering
About the role
Responsibilities
Design and train Vision-Language-Action (VLA) solutions for robotaxis
Lead end-to-end data strategy, including mining, auto-labeling, and dataset construction to power our ML flywheel
Lead the full post-training stack for VLMs and VLAs, including Continual Pre-training (CPT) on domain-specific driving data, Supervised Fine-Tuning (SFT) for instruction following
Utilize our large-scale data pipelines and ML infrastructure to research, prototype, and deploy solutions that improve driving behavior
Partner with cross-functional teams to integrate perception signals
Qualifications
MS or PhD in Computer Science or related field
Background in deep learning solutions for VLM and VLA models
Track record in post-training large-scale models, CPT, SFT, RL
Hands-on experience with production ML pipelines, including dataset creation, training frameworks, and metrics
Expertise in Python libraries (PyTorch, NumPy, Pandas, VLLM)
Bonus Qualifications
Deep knowledge of cutting-edge computer vision techniques
Publications in top-tier conferences (CVPR, ICCV, RSS, ICRA)
Experience with integrating large language models to various tasks
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